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Found 5 papers, 3 papers with code
Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving
To this end, we propose a two-stage weakly supervised approach, where the segmentation model trained with the incomplete binary masks in Stage1 will facilitate the self-supervised learning of the motion prediction network in Stage2 by estimating possible moving foregrounds in advance.
Weakly Supervised Segmentation on Outdoor 4D Point Clouds With Temporal Matching and Spatial Graph Propagation
We propose a novel temporal-spatial framework for effective weakly supervised learning to generate high-quality pseudo labels from these limited annotated data.
Lumen: A Machine Learning Framework to Expose Influence Cues in Text
Phishing and disinformation are popular social engineering attacks with attackers invariably applying influence cues in texts to make them more appealing to users.
SpSequenceNet: Semantic Segmentation Network on 4D Point Clouds
Point clouds are useful in many applications like autonomous driving and robotics as they provide natural 3D information of the surrounding environments.
A new evaluation framework for topic modeling algorithms based on synthetic corpora
Topic models are in widespread use in natural language processing and beyond.
